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                <h1 class="ft-40 bold black mb-3 md-md-5">Benefits & Use Cases</h1>
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                    <p>A graph is a structure composed of vertices and edges. Both vertices and edges can have an
                        arbitrary number of key/value-pairs called properties. Vertices denote discrete objects such as
                        a person, a place, or an event. Edges denote relationships between vertices. For instance, a
                        person may know another person, have been involved in an event, and/or have recently been at a
                        particular place. Properties express non-relational information about the vertices and edges.
                        Example properties include a vertex having a name and an age, and an edge having a timestamp
                        and/or a weight. Together, the aforementioned graph is known as a property graph and it is the
                        foundational data structure of Apache TinkerPop. </p>
                    <p>If a user's domain is composed of a heterogeneous set of objects (vertices) that can be related
                        to one another in a multitude of ways (edges), then a graph may be the right representation to
                        use. In a graph, each vertex is seen as an atomic entity (not simply a "row in a table") that
                        can be linked to any other vertex or have properties added or removed at will. This empowers the
                        data modeler to think in terms of actors within a world of complex relations as opposed to, in
                        relational databases, statically-typed tables joined in aggregate. Once a domain is modeled,
                        that model must then be exploited in order to yield novel, differentiating information. Graph
                        computing has a rich history that includes not only query languages devoid of table-join
                        semantics, but also algorithms that support complex reasoning: path analysis, vertex clustering
                        and ranking, subgraph identification, and more. The world of applied graph computing offers a
                        flexible, intuitive data structure along with a host of algorithms able to effectively leverage
                        that structure.</p>
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                <h2 class="ft-30 bold black mb-4">Use Cases</h2>
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                    <h3 class="ft-18 bold text-blue">Social Networks</h3>
                    <p>Unleash the power of a social network by using relationships between individuals to infer and
                        recommend connections.</p>
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                    <p>Leverage the connections inherent in a financial transaction to provide real-time analysis and
                        detection for known fraudulent patterns of activity.</p>
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                    <h3 class="ft-18 bold text-blue">Knowledge Graphs</h3>
                    <p>Unite disperate data sources and data silos to provide contextually relevant information to
                        queries.</p>
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                    <h3 class="ft-18 bold text-blue">Recommendation Engines</h3>
                    <p>Provide real-time personalized recommendations for products, services and content by utilizing
                        connections within data.</p>
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                    <h3 class="ft-18 bold text-blue">Identity/Access Management</h3>
                    <p>Effectively and effciently track user activity and access using a graph of assets and
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                    <p>Leverage disconnected data sources to provide a holisitic 360 degree view of customer
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                    <p>Organize and provide access to canonical master data by combining data in a schemaless and
                        flexible manner.</p>
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                    <h3 class="ft-18 bold text-blue">Supply Chain Management</h3>
                    <p>Manage and visualize complex interconnected supply chains to identify optimizations and assess
                        risk.</p>
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                    <h3 class="ft-18 bold text-blue">Compliance</h3>
                    <p>Ensure effective compliance by examining and evaluating entities against a network of applicable
                        interconnected regulations.</p>
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